More generally, our technique works for \(M\) -estimators, a general class of clustering objectives that includes the well-known \(k\) -median and \(k\) -means functions as special cases. Other special cases include the Cauchy functions, the Tukey functions, and the \(L_p\)  norms.
Our method combines a streaming bicriterion algorithm [1]} and a batch coreset construction [2]} to create a streaming coreset algorithm. The space requirements are combined addivitely, therefore ensuring no overhead.
